Winning Picks, Guaranteed
S p o r t s D a t a b a s e . c o m
tools    for    the    objective    handicapper


name
password


NHL Trends SDB Home    NHL Trends    NHL Query
Include trends from SDB's sample ml against SDB's sample ml on SDB's sample ou against SDB's sample ou on SDB's sample su active on filter on
Trends from SDB's sample ou against,SDB's sample ou on,SDB's sample ou against,SDB's sample ou on
$ ROI wins losses % link
1540 36.7 11 24 31.4 The Predators are 11-24-7 AGAINST since Mar 11, 2017
1040 49.5 5 14 26.3 The Predators are 5-14-2 AGAINST since Mar 20, 2017 as a favorite
1030 51.5 4 13 23.5 The Predators are 4-13-3 AGAINST since Mar 20, 2017 at home
1030 54.2 4 13 23.5 The Predators are 4-13-2 AGAINST since Mar 20, 2017 as a home favorite
710 32.3 5 11 31.2 The Predators are 5-11-6 AGAINST since Mar 02, 2017 as a dog
710 33.8 5 11 31.2 The Predators are 5-11-5 AGAINST since Mar 02, 2017 as a road dog
620 25.8 7 12 36.8 The Predators are 7-12-5 AGAINST since Mar 02, 2017 on the road
510 26.8 11 7 61.1 The Predators are 11-7-1 ON since Mar 05, 2016 as a road favorite

Trend Parameters: active, english, invested, losses, margin, profit, pushes, sdql, start, team, wins


How To Use the Trends Page:
Use the Pythonic Query Language to explore a database of trends. The full PyQL format is: parameters @ conditions. More typical use just specifies the condition and takes a default output.

To see all trends with an average margin of at least 2 use the PyQL condition: margin > 2.

To see all perfect trends use the PyQL: wins * losses = 0
e-mail links:   Content@SportsDataBase.com    Support@SportsDataBase.com   
Content for this site is generated using the Sports Data Query Language (SDQL).